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Kantorovich theorem

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Through Fixed point (mathematics), Differentiable function and Linear programming

Newton's method constructs a sequence of points that under certain conditions will converge to a solution x of an equation f(x)=0 or a vector solution of a system of equation F(x)=0. The Kantorovich theorem gives conditions on the initial point of this sequence. If those conditions are satisfied then a solution exists close to the initial point and the sequence converges to that point.

Assumptions

Let X⊂Rn be an open subset and F:X⊂Rn→Rn a differentiable function with a Jacobian F′(x) that is locally Lipschitz continuous (for instance if F is twice differentiable). That is, it is assumed that for any x∈X there is an open subset U⊂X such that x∈U and there exists a constant L>0 such that for any x,y∈U

‖F′(x)−F′(y)‖≤L‖x−y‖

holds. The norm on the left is the operator norm. In other words, for any vector v∈Rn the inequality

‖F′(x)(v)−F′(y)(v)‖≤L‖x−y‖‖v‖

must hold.

Now choose any initial point x0∈X. Assume that F′(x0) is invertible and construct the Newton step h0=−F′(x0)−1F(x0).

The next assumption is that not only the next point x1=x0+h0 but the entire ball B(x1,‖h0‖) is contained inside the set X. Let M be the Lipschitz constant for the Jacobian over this ball (assuming it exists).

As a last preparation, construct recursively, as long as it is possible, the sequences (xk)k, (hk)k, (αk)k according to

hk=−F′(xk)−1F(xk)αk=M‖F′(xk)−1‖‖hk‖xk+1=xk+hk.

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